Design principles for text-to-image generative artificial intelligence creativity support tools for visual design

Generative AI (GenAI) presents significant opportunities, particularly for creative work like visual design. GenAI can effectively address creative challenges like the "blank page" problem by enabling rapid visual conceptualisation, thereby enhancing productivity in visual design tasks. However, organisations face significant challenges in integrating off-the-shelf, untamed foundation models, whose complex user interfaces are misaligned with production-oriented workflows, exacerbating issues such as AI illiteracy, employee resistance, and job displacement. To facilitate GenAI integration into creative workflows while addressing these challenges, we conduct an action design research study at Ubisoft, where we develop and introduce a GenAI-enabled creativity support tool (CST)-comprising workflow guidance and simplified user interface on Stable Diffusion models-as a bridging tool in concept art creation processes. Our user studies and evaluations indicate that the artefact increases user acceptance, improves productivity, and adds value to both concept artists and their studios. In addition to detailing the artefact's design and evaluation, we present seven design principles for text-to-image GenAI CSTs for visual design. These principles contribute to the academic discourse on human-AI collaboration by filling a critical gap in prescriptive design knowledge and emphasising the role of GenAI in augmenting, rather than replacing, human skill and ingenuity.

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Publication Details

Journal
European Journal of Information Systems
Published
2026-01-20
DOI
https://doi.org/10.1080/0960085x.2026.2616042
Citations
1
Primary Topic
Design Education and Practice
Type
article
Field-Weighted Citation Impact
19.05
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article

Design principles for text-to-image generative artificial intelligence creativity support tools for visual design

Amirsiavosh Bashardoust, Yash Raj Shrestha, Yonah Bole, Savindu Herath
1 citations
European Journal of Information Systems
Design Education and Practice
19.05
article

Design principles for text-to-image generative artificial intelligence creativity support tools for visual design

Amirsiavosh Bashardoust, Yash Raj Shrestha, Yonah Bole, Savindu Herath
article en
1 citations

Abstract

Generative AI (GenAI) presents significant opportunities, particularly for creative work like visual design. GenAI can effectively address creative challenges like the "blank page" problem by enabling rapid visual conceptualisation, thereby enhancing productivity in visual design tasks. However, organisations face significant challenges in integrating off-the-shelf, untamed foundation models, whose complex user interfaces are misaligned with production-oriented workflows, exacerbating issues such as AI illiteracy, employee resistance, and job displacement. To facilitate GenAI integration into creative workflows while addressing these challenges, we conduct an action design research study at Ubisoft, where we develop and introduce a GenAI-enabled creativity support tool (CST)-comprising workflow guidance and simplified user interface on Stable Diffusion models-as a bridging tool in concept art creation processes. Our user studies and evaluations indicate that the artefact increases user acceptance, improves productivity, and adds value to both concept artists and their studios. In addition to detailing the artefact's design and evaluation, we present seven design principles for text-to-image GenAI CSTs for visual design. These principles contribute to the academic discourse on human-AI collaboration by filling a critical gap in prescriptive design knowledge and emphasising the role of GenAI in augmenting, rather than replacing, human skill and ingenuity.

European Journal of Information Systems
ETH Zurich (CH), University of Lausanne (CH)
Openalex Percentile: Top 2%
Design Education and Practice
19.05
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Design principles for text-to-image generative artificial intelligence creativity support tools for visual design — Amirsiavosh Bashardoust, Yash Raj Shrestha, et al. · European Journal of Information Systems (2026) | TGRS Research Map | TGRS